JUN 25, 2019 10:00 PM PDT

Scientists use AI to reveal an unexpected role for "junk" DNA in autism

WRITTEN BY: Nina Lichtenberg

According to a new study published in Nature Genetics, spontaneous mutations or "junk" DNA that occur between genes may turn out to be key to understanding autism. This study was the first to examine the impact of these 'noncoding' mutations across the entire genome of autistic individuals.

Over the past three years, several research teams have sequenced the DNA of autistic people both within and between genes. However, sorting through thousands and thousands of mutations between genes has proved extremely challenging.

In a recent study led by Princeton professor Olga Troyanskaya, deputy director for genomics at the Flatiron Institute's Center for Computational Biology in New York City, and collaborators researchers overcame this challenge by using artificial intelligence (AI) deep learning to identify the contribution of noncoding mutations to autism risk.

In the study, scientists created an algorithm to predict whether a certain noncoding mutation alters any gene's expression. The algorithm assigns each mutation a score which indicates how likely it is to alter gene expression, and therefore, how harmful it is.

The study is particularly strong because it examines spontaneous mutations across the whole genome.

Prior effects tend to analyze noncoding mutations within a certain region of the genome, typically those closest to the gene of interest, says professor Xin He, assistant professor of genetics at the University of Chicago, who was not involved in the study.

Troyanskaya's team and her colleagues analyzed 7,097 whole genomes from 1,790 families that have one autistic child but normal parents and at least one unaffected sibling. They found thousands of spontaneous mutations in the autistic children, but approximately the same number in unaffected children.

Then, the team searched through the Human Gene Mutation Database to check whether the mutations had known links to medical conditions or appeared in healthy individuals. They gathered all of this information to generate an impact score for each mutation.

Researchers found that noncoding mutations in children with autism had greater impact cores than those of their unaffected siblings. Interestingly, in a follow-up study on the high-impact noncoding mutations in autistic children were expressed in brain tissue. Thus, the study may indicate that such noncoding regulatory elements in the developing brain may contribute to autism, as well as other neurodevelopmental disorders.

Now, Troyanskaya and her colleagues are applying the algorithm, called DeepSEA, to whole genomes of individuals with other medical conditions such as heart disease.

Source: Scientific American, Psychology Today

About the Author
You May Also Like
DEC 22, 2019
Neuroscience
DEC 22, 2019
Midlife Obesity, not Diet, Increases Dementia Risk
A new study on over 1 milion women in the UK has found that women who are obese during their 50’s are at a higher risk than women with healthier phys...
DEC 25, 2019
Neuroscience
DEC 25, 2019
Air Pollution Linked to Depression and Suicide
Living amid high levels of air pollution increases one’s risk of developing depression and commiting suicide, says new research from University Colle...
JAN 06, 2020
Cardiology
JAN 06, 2020
Online Therapy Treats Depression in Heart Disease Patients
People suffering from cardiovascular disease (CVD) often suffer from depression too- something that can lead to a vicious cycle in which CVD can be negativ...
JAN 05, 2020
Neuroscience
JAN 05, 2020
Memory Recall Linked to Circadian Rhythm
  A study from the University of Tokyo identified a specific gene responsible for memory retrieval in mice. The study aimed to investigate the biology...
FEB 26, 2020
Genetics & Genomics
FEB 26, 2020
Optogenetic Techniques Provide Insight Into ALS
In humans, motor neurons link thoughts with the motion of the body. Now researchers have learned more about how they are impacted by ALS....
MAR 24, 2020
Neuroscience
MAR 24, 2020
Researchers Use Silicon to Record Electrical Signals Between Neurons
Researchers from Stanford University have created a way to connect the brain directly to silicon-based technologies. Hoping to assist the development of me...
Loading Comments...